Mark rate exploration
Methods
- We pulled raw recreational catch data from CREST database: data sources include creel, iREC, lodge and log-book data. Data is typically in number of marked and unmarked fish kept and released.
- Filtered the creel data based on high quality creel which meet the following criteria in a given PFMA and month:
- At least 3 flights for each type of day (weekday or weekend)
- At least 25 interviews mid week OR at least 10% of interviews from mid-week
- At least 25 interviews on weekends OR at least 10% of interviews from weekend
- At least 15 day spread in flights
- At least 15 day spread in interviews
- We calculated mark rate for each data source based on number of marked and unmarked fish encountered. We created a cut-off of data for n=100 fish in a given month. If the sample was less than that then there wasn’t enough data to create a mark-rate estimate.
Then we calculated an average of mark rate for the five year 2019-2023 period and one for the five year 2014-2018 period for each source.
After the averages were calculated, we combined data sources using the following rule:
In months 5-9 use creel+ lodge if that data exists, otherwise use iREC
In months outside of 5-9 use iREC
We included commercial troll data but this did not fill out the data frame any more than using only creel and iREC
Results
Heat Map
iREC & creel data combined 2019-current by catch region
- Pink borders indicate the estimate includes data from iREC, without the border is creel-only information
iREC & creel data combined 2019-current
- Pink borders indicate the estimate includes data from iREC, without the border is creel-only information
iREC & creel data combined 2014-2018
iREC & creel data combined 2014-2018 Catch region
Individual data sets
Datasets for 2019-2023 separated out by source.
Plots over time
Re-created these using the “best practices” combo of creel and irec